Artificial intelligence at the national eye institute

Noha A. Sherif, Emily Y. Chew, Michael F. Chiang, Michelle Hribar, James Gao, Kerry E. Goetz

Research output: Contribution to journalReview articlepeer-review


Purpose of reviewThis review highlights the artificial intelligence, machine learning, and deep learning initiatives supported by the National Institutes of Health (NIH) and the National Eye Institute (NEI) and calls attention to activities and goals defined in the NEI Strategic Plan as well as opportunities for future activities and breakthroughs in ophthalmology.Recent findingsOphthalmology is at the forefront of artificial intelligence-based innovations in biomedical research that may lead to improvement in early detection and surveillance of ocular disease, prediction of progression, and improved quality of life. Technological advances have ushered in an era where unprecedented amounts of information can be linked that enable scientific discovery. However, there remains an unmet need to collect, harmonize, and share data in a machine actionable manner. Similarly, there is a need to ensure that efforts promote health and research equity by expanding diversity in the data and workforce.SummaryThe NIH/NEI has supported the development artificial intelligence-based innovations to advance biomedical research. The NIH/NEI has defined activities to achieve these goals in the NIH Strategic Plan for Data Science and the NEI Strategic Plan and have spearheaded initiatives to facilitate research in these areas.

Original languageEnglish (US)
Pages (from-to)579-584
Number of pages6
JournalCurrent opinion in ophthalmology
Issue number6
StatePublished - Nov 1 2022


  • artificial intelligence
  • bioinformatics
  • data science
  • national eye institute
  • national institutes of health

ASJC Scopus subject areas

  • Ophthalmology


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